An autonomous robot vehicle in accordance with aspects of the present disclosure includes a land vehicle conveyance system, a communication system configured to communicate with a remote human operator system, one or more processors, and a memory storing instructions. The instructions, when executed by the processor(s), cause the autonomous robot vehicle to receive via the communication system control instructions from the remote human operator system for controlling the land vehicle conveyance system, control the land vehicle conveyance system in accordance with the control instructions to perform travel, and autonomously control the land vehicle conveyance system in coordination with the control instructions from the remote human operator system to semi-autonomously perform travel.

A system for a mobile secure locker in accordance with aspects of the present disclosure includes processor(s) and memory storing instructions. The instructions, when executed by the processor(s), cause the system to provide a user interface for a user to rent a mobile secure locker in an autonomous robot vehicle, receive information through the user interface from the user where the information includes a first destination, a second destination, and a time associated with the second destination, communicate instructions to the autonomous robot vehicle to travel to the first destination to receive the item, receive an indication from the autonomous robot vehicle that the item has been received, communicate instructions to the autonomous robot vehicle to travel to the second destination to deliver the item to the user at the time associated with the second destination, and receive from the autonomous robot vehicle an indication the item is retrieved.

The present invention relates to an autonomous vehicle and an autonomous vehicle system having the same. The autonomous vehicle according to the present invention comprises: a plurality of cameras; a radar; a communication unit; a display; an audio output unit; and a processor which, in an autonomous driving mode, controls the autonomous vehicle so as to select any one of a plurality of routes toward a destination and perform autonomous driving along the selected route, to receive advertisement information from the outside when driving along the selected route, and to output the received advertisement information through at least one of a display or an audio output unit, the received advertisement information being variable for each of the plurality of routes. Due to this feature, it is possible to provide different advertisements for each route to the destination during autonomous driving.

Provided herein is an autonomous or semi-autonomous vehicle fleet comprising a plurality of electric autonomous vehicle for apportioned display of a media, operating autonomously and a fleet management module for coordination of the autonomous vehicle fleet. Each autonomous or semi-autonomous vehicle comprising a screen configured to display the media. Activation, deactivation, brightness modification, in combination with specific media selection enables more efficient media display.

Transportation systems have artificial intelligence including neural networks for recognition and classification of objects and behavior including natural language processing and computer vision systems. The transportation systems involve sets of complex chemical processes, mechanical systems, and interactions with behaviors of operators. System-level interactions and behaviors are classified, predicted and optimized using neural networks and other artificial intelligence systems through selective deployment, as well as hybrids and combinations of the artificial intelligence systems, neural networks, expert systems, cognitive systems, genetic algorithms and deep learning.

The server is configured to communicate with a plurality of power-supplying vehicles and a plurality of power-receiving vehicles. The server is configured to notify, to matched vehicles (candidate power-receiving vehicle and candidate power-supplying vehicle), a candidate gathering location list including respective pieces of information of a plurality of parking areas owned by third parties different from users of the matched vehicles, so as to make an inquiry to the users of the matched vehicles to select one of the plurality of parking areas included in the candidate gathering location list. The server is configured to determine a gathering location for the matched vehicles using the respective pieces of information of the parking areas selected by the users of the matched vehicles, and is configured to transmit the information of the parking area of the determined gathering location to the matched vehicles.

Systems and methods for negotiating media payments paid to a consumer traveling in a vehicle include delivering sponsored media content to a device in the vehicle. In exchange for listening to the sponsored media content, a media payment is transmitted to a financial account associated with the user. In some embodiments, the media payment is higher when the sponsored media content has more geographic relevance to the consumer's location in the vehicle.

Transportation systems have artificial intelligence including neural networks for recognition and classification of objects and behavior including natural language processing and computer vision systems. The transportation systems involve sets of complex chemical processes, mechanical systems, and interactions with behaviors of operators. System-level interactions and behaviors are classified, predicted and optimized using neural networks and other artificial intelligence systems through selective deployment, as well as hybrids and combinations of the artificial intelligence systems, neural networks, expert systems, cognitive systems, genetic algorithms and deep learning.

Transportation systems have artificial intelligence including neural networks for recognition and classification of objects and behavior including natural language processing and computer vision systems. The transportation systems involve sets of complex chemical processes, mechanical systems, and interactions with behaviors of operators. System-level interactions and behaviors are classified, predicted and optimized using neural networks and other artificial intelligence systems through selective deployment, as well as hybrids and combinations of the artificial intelligence systems, neural networks, expert systems, cognitive systems, genetic algorithms and deep learning.

Transportation systems have artificial intelligence including neural networks for recognition and classification of objects and behavior including natural language processing and computer vision systems. The transportation systems involve sets of complex chemical processes, mechanical systems, and interactions with behaviors of operators. System-level interactions and behaviors are classified, predicted and optimized using neural networks and other artificial intelligence systems through selective deployment, as well as hybrids and combinations of the artificial intelligence systems, neural networks, expert systems, cognitive systems, genetic algorithms and deep learning.